ArticleNPJ digital medicine2021
Wearable sensor derived decompensation index for continuous remote monitoring of COVID-19 diagnosed patients.
Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Artificial intelligence in urology: Revolutionizing diagnostics and treatment planning.Arab journal of urology · 2025Review
- Review
- Predictive Data Analytics in Telecare and Telehealth: Systematic Scoping Review.Online journal of public health informatics · 2024Article
- Remote digital health technologies for improving the care of people with respiratory disorders.The Lancet. Digital health · 2024Review
- Utilizing Wearable Device Data for Syndromic Surveillance: A Fever Detection Approach.Sensors (Basel, Switzerland) · 2024Article
- Using a wearable patch to develop a digital monitoring biomarker of inflammation in response to LPS challenge.Clinical and translational science · 2024Article
- Evaluating an Advanced Practice Provider-Managed Coronavirus Disease 2019 Deterioration Program.The journal for nurse practitioners : JNP · 2023Article
- A Call to Expand the Scope of Digital Phenotyping.Journal of medical Internet research · 2023Article
- Discovery of associative patterns between workplace sound level and physiological wellbeing using wearable devices and empirical Bayes modeling.NPJ digital medicine · 2023Article
- Real-Time Prediction of Mortality, Cardiac Arrest, and Thromboembolic Complications in Hospitalized Patients With COVID-19.JACC. Advances · 2022Article
- Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression.Cell reports. Medicine · 2022Article
- Methods for detecting probable COVID-19 cases from large-scale survey data also reveal probable sex differences in symptom profiles.Frontiers in big data · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The COVID-19 pandemic has accelerated the adoption of innovative healthcare methods, including remote patient monitoring. In the setting of limited healthcare resources, outpatient management of individuals newly diagnosed with COVID-19 was commonly implemented, some taking advantage of various personal health technologies, but only rarely using a multi-parameter chest-patch for continuous monitoring. Here we describe the development and validation of a COVID-19 decompensation index (CDI) model based on chest patch-derived continuous sensor data to predict COVID-19 hospitalizations in outpatient-managed COVID-19 positive individuals, achieving an overall AUC of the ROC Curve of 0.84 on 308 event negative participants, and 22 event positive participants, out of an overall study cohort of 400 participants. We retrospectively compare the performance of CDI to standard of care modalities, finding that the machine learning model outperforms the standard of care modalities in terms of both numbers of events identified and with a lower false alarm rate. While only a pilot phase study, the CDI represents a promising application of machine learning within a continuous remote patient monitoring system.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.